Classification of Optical‐Sensor Response Cues with a Bi‐dimensional Wavelet‐Transform Approach Available to Purchase

In this work is used the two‐dimensional discrete wavelet transform as a feature extractor of time responses from a porous silicon optical gas sensor for gas identification. The wavelet decomposition allows us to have a more in‐deep sight of the sensor response. In addition, using a linear support vector machine (SVM) as classifier we evaluate our approach for a six‐analyte discrimination problem.